{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Wells\n",
    "\n",
    "**Wells are one of the fundamental objects in `welly`.**\n",
    "\n",
    "`Well` objects include collections of `Curve` objects. Multiple `Well` objects can be stored in a `Project`.\n",
    "\n",
    "On this page, we take a closer look at the `Well`.\n",
    "\n",
    "First, some preliminaries..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.5.3.dev10+gf4a190d.d20220412'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import welly\n",
    "welly.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load a well from LAS\n",
    "\n",
    "In the Quick Start guide you saw how to quickly create a Project from a well with:\n",
    "\n",
    "```python\n",
    "import welly\n",
    "project = welly.from_las('path/to/well.las')\n",
    "```\n",
    "\n",
    "A `welly.Project` is a collection of `welly.Well` objects. But if you only have a single well, you may not need a Project; a Well object on its own will do. Then you could do this:\n",
    "\n",
    "```python\n",
    "well, = welly.from_las('path/to/well.las')\n",
    "```\n",
    "\n",
    "The presence of the comma after `well` unpacks the single item into the `welly` variable. (This is a Python trick, it's not a Welly thing.)\n",
    "\n",
    "Alternatively, you can use the `Well.from_las()` method to load a well by passing a filename as a `str`. This is really just a wrapper for `lasio` but instantiates a `Header`, `Curve`s, etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Only engine='normal' can read wrapped files\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table><tr><th style=\"text-align:center;\" colspan=\"2\">Kennetcook #2<br><small>Long = 63* 45'24.460  W</small></th></tr><tr><td><strong>crs</strong></td><td>CRS({})</td></tr><tr><td><strong>location</strong></td><td>Lat = 45* 12' 34.237\" N</td></tr><tr><td><strong>country</strong></td><td>CA</td></tr><tr><td><strong>province</strong></td><td>Nova Scotia</td></tr><tr><td><strong>latitude</strong></td><td></td></tr><tr><td><strong>longitude</strong></td><td></td></tr><tr><td><strong>datum</strong></td><td></td></tr><tr><td><strong>section</strong></td><td>45.20 Deg N</td></tr><tr><td><strong>range</strong></td><td>PD 176</td></tr><tr><td><strong>township</strong></td><td>63.75 Deg W</td></tr><tr><td><strong>ekb</strong></td><td>94.8</td></tr><tr><td><strong>egl</strong></td><td>90.3</td></tr><tr><td><strong>gl</strong></td><td>90.3</td></tr><tr><td><strong>tdd</strong></td><td>1935.0</td></tr><tr><td><strong>tdl</strong></td><td>1935.0</td></tr><tr><td><strong>td</strong></td><td>None</td></tr><tr><td><strong>data</strong></td><td>CALI, DPHI_DOL, DPHI_LIM, DPHI_SAN, DRHO, DT, DTS, GR, HCAL, NPHI_DOL, NPHI_LIM, NPHI_SAN, PEF, RHOB, RLA1, RLA2, RLA3, RLA4, RLA5, RM_HRLT, RT_HRLT, RXOZ, RXO_HRLT, SP</td></tr></table>"
      ],
      "text/plain": [
       "Well(uwi: 'Long = 63* 45'24.460  W', name: 'Kennetcook #2', 24 curves: ['CALI', 'HCAL', 'PEF', 'DT', 'DTS', 'DPHI_SAN', 'DPHI_LIM', 'DPHI_DOL', 'NPHI_SAN', 'NPHI_LIM', 'NPHI_DOL', 'RLA5', 'RLA3', 'RLA4', 'RLA1', 'RLA2', 'RXOZ', 'RXO_HRLT', 'RT_HRLT', 'RM_HRLT', 'DRHO', 'RHOB', 'GR', 'SP'])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from welly import Well\n",
    "\n",
    "p129 = Well.from_las('https://geocomp.s3.amazonaws.com/data/P-129.LAS')\n",
    "p129"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are a lot of problems here:\n",
    "\n",
    "- The Location is not stored correctly, with latitude stored in Location and Longitude stored in UWI (that's why it appears in the title row of this view).\n",
    "- There's less accurate Lat and Lon information stored in Section and Township; we should get rid of those.\n",
    "- There's no UWI, KB or TD, all of which would be useful to populate.\n",
    "\n",
    "We can fix all this by 'remapping' some fields. This is done with a dictionary that maps a well's field to its location in the LAS file. For example, we can use the Well field ('Kennetcook #2') to as the UWI in our well with a mapping like: `{'UWI': 'WELL'}`. We can remove a bad item such as the Section name, by mapping to `None`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Only engine='normal' can read wrapped files\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table><tr><th style=\"text-align:center;\" colspan=\"2\">Kennetcook #2<br><small>P-129</small></th></tr><tr><td><strong>crs</strong></td><td>CRS({})</td></tr><tr><td><strong>country</strong></td><td>CA</td></tr><tr><td><strong>province</strong></td><td>Nova Scotia</td></tr><tr><td><strong>latitude</strong></td><td>Lat = 45* 12' 34.237\" N</td></tr><tr><td><strong>longitude</strong></td><td>Long = 63* 45'24.460  W</td></tr><tr><td><strong>datum</strong></td><td></td></tr><tr><td><strong>range</strong></td><td>PD 176</td></tr><tr><td><strong>ekb</strong></td><td>94.8</td></tr><tr><td><strong>egl</strong></td><td>90.3</td></tr><tr><td><strong>kb</strong></td><td>94.8</td></tr><tr><td><strong>gl</strong></td><td>90.3</td></tr><tr><td><strong>td</strong></td><td>1935.0</td></tr><tr><td><strong>tdd</strong></td><td>1935.0</td></tr><tr><td><strong>tdl</strong></td><td>1935.0</td></tr><tr><td><strong>data</strong></td><td>CALI, DPHI_DOL, DPHI_LIM, DPHI_SAN, DRHO, DT, DTS, GR, HCAL, NPHI_DOL, NPHI_LIM, NPHI_SAN, PEF, RHOB, RLA1, RLA2, RLA3, RLA4, RLA5, RM_HRLT, RT_HRLT, RXOZ, RXO_HRLT, SP</td></tr></table>"
      ],
      "text/plain": [
       "Well(uwi: 'P-129', name: 'Kennetcook #2', 24 curves: ['CALI', 'HCAL', 'PEF', 'DT', 'DTS', 'DPHI_SAN', 'DPHI_LIM', 'DPHI_DOL', 'NPHI_SAN', 'NPHI_LIM', 'NPHI_DOL', 'RLA5', 'RLA3', 'RLA4', 'RLA1', 'RLA2', 'RXOZ', 'RXO_HRLT', 'RT_HRLT', 'RM_HRLT', 'DRHO', 'RHOB', 'GR', 'SP'])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "remap = {\n",
    "    'UWI': 'LIC',  # Commonly used unique name; not a true UWI.\n",
    "    'KB': 'EKB',\n",
    "    'TD': 'TDD',  # Driller's TD.\n",
    "    'LATI': 'LOC',\n",
    "    'LONG': 'UWI',\n",
    "    'SECT': None,\n",
    "    'TOWN': None,\n",
    "    'LOC': None\n",
    "}\n",
    "\n",
    "p129 = Well.from_las('https://geocomp.s3.amazonaws.com/data/P-129.LAS', remap=remap)\n",
    "p129"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That's better!\n",
    "\n",
    "Later on, we'll look at how we can go a step further, extracting the more accurate "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Well header\n",
    "\n",
    "Metadata about the well is stored in its `header` attribute:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>original_mnemonic</th>\n",
       "      <th>mnemonic</th>\n",
       "      <th>unit</th>\n",
       "      <th>value</th>\n",
       "      <th>descr</th>\n",
       "      <th>section</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>VERS</td>\n",
       "      <td>VERS</td>\n",
       "      <td></td>\n",
       "      <td>2.0</td>\n",
       "      <td></td>\n",
       "      <td>Version</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>WRAP</td>\n",
       "      <td>WRAP</td>\n",
       "      <td></td>\n",
       "      <td>YES</td>\n",
       "      <td></td>\n",
       "      <td>Version</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>STRT</td>\n",
       "      <td>STRT</td>\n",
       "      <td>M</td>\n",
       "      <td>1.0668</td>\n",
       "      <td>START DEPTH</td>\n",
       "      <td>Well</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>STOP</td>\n",
       "      <td>STOP</td>\n",
       "      <td>M</td>\n",
       "      <td>1939.1376</td>\n",
       "      <td>STOP DEPTH</td>\n",
       "      <td>Well</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>STEP</td>\n",
       "      <td>STEP</td>\n",
       "      <td>M</td>\n",
       "      <td>0.1524</td>\n",
       "      <td>STEP</td>\n",
       "      <td>Well</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>TLI</td>\n",
       "      <td>TLI</td>\n",
       "      <td>M</td>\n",
       "      <td>280.0</td>\n",
       "      <td>Top Log Interval</td>\n",
       "      <td>Parameter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>UWID</td>\n",
       "      <td>UWID</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Unique Well Identification Number</td>\n",
       "      <td>Parameter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>WN</td>\n",
       "      <td>WN</td>\n",
       "      <td></td>\n",
       "      <td>Kennetcook #2</td>\n",
       "      <td>Well Name</td>\n",
       "      <td>Parameter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>EPD</td>\n",
       "      <td>EPD</td>\n",
       "      <td>M</td>\n",
       "      <td>90.300003</td>\n",
       "      <td>Elevation of Permanent Datum above Mean Sea Level</td>\n",
       "      <td>Parameter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td></td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>142 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    original_mnemonic mnemonic unit          value  \\\n",
       "0                VERS     VERS                 2.0   \n",
       "1                WRAP     WRAP                 YES   \n",
       "2                STRT     STRT    M         1.0668   \n",
       "3                STOP     STOP    M      1939.1376   \n",
       "4                STEP     STEP    M         0.1524   \n",
       "..                ...      ...  ...            ...   \n",
       "137               TLI      TLI    M          280.0   \n",
       "138              UWID     UWID                       \n",
       "139                WN       WN       Kennetcook #2   \n",
       "140               EPD      EPD    M      90.300003   \n",
       "141                    UNKNOWN                       \n",
       "\n",
       "                                                 descr    section  \n",
       "0                                                         Version  \n",
       "1                                                         Version  \n",
       "2                                          START DEPTH       Well  \n",
       "3                                           STOP DEPTH       Well  \n",
       "4                                                 STEP       Well  \n",
       "..                                                 ...        ...  \n",
       "137                                   Top Log Interval  Parameter  \n",
       "138                  Unique Well Identification Number  Parameter  \n",
       "139                                          Well Name  Parameter  \n",
       "140  Elevation of Permanent Datum above Mean Sea Level  Parameter  \n",
       "141                                                         Other  \n",
       "\n",
       "[142 rows x 6 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p129.header"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Important note\n",
    "\n",
    "At present, the well's `header` contains a DataFrame with the entire LAS file header.\n",
    "\n",
    "In a future release, only the well information from the **WELL** part of the file will be stored in the well's header. (The Params data goes into the `well.location` attribute, and the Curve data goes into Welly's `Curve` objects.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Well location\n",
    "\n",
    "The well's `location` contains the location info from **PARAMS**, and will also store the well's 3D positional information, if available."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Location({'position': None, 'crs': CRS({}), 'country': 'CA', 'province': 'Nova Scotia', 'latitude': 'Lat = 45* 12\\' 34.237\" N', 'longitude': \"Long = 63* 45'24.460  W\", 'datum': '', 'range': 'PD 176', 'ekb': 94.8, 'egl': 90.3, 'kb': 94.8, 'gl': 90.3, 'td': 1935.0, 'tdd': 1935.0, 'tdl': 1935.0, 'deviation': None})"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p129.location"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The CRS for this well is missing; we can add one if we know it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Location({'position': None, 'crs': CRS({'init': 'epsg:2038', 'no_defs': True}), 'country': 'CA', 'province': 'Nova Scotia', 'latitude': 'Lat = 45* 12\\' 34.237\" N', 'longitude': \"Long = 63* 45'24.460  W\", 'datum': '', 'range': 'PD 176', 'ekb': 94.8, 'egl': 90.3, 'kb': 94.8, 'gl': 90.3, 'td': 1935.0, 'tdd': 1935.0, 'tdl': 1935.0, 'deviation': None})"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p129.location.crs = welly.CRS.from_epsg(2038)\n",
    "\n",
    "p129.location"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Right now there's no position log — we need to load a deviation survey."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "p129.location.position"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add deviation data to a well\n",
    "\n",
    "Let's load another well:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from welly import Well\n",
    "\n",
    "p130 = Well.from_las('https://geocomp.s3.amazonaws.com/data/P-130.LAS')\n",
    "\n",
    "dev = np.loadtxt('https://geocomp.s3.amazonaws.com/data/P-130_deviation_survey.csv',\n",
    "                 delimiter=',', skiprows=1\n",
    "                )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The columns are MD, inclination, azimuth, and TVD."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 18. ,   0.3,   0. ,  18. ],\n",
       "       [ 38. ,   0.5,   0. ,  38. ],\n",
       "       [ 57. ,   1.5,   0. ,  57. ],\n",
       "       [ 84. ,   1.8,   0. ,  84. ],\n",
       "       [104. ,   0.5,   0. , 104. ]])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dev[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`add_deviation` wants only MD, inclination and azimuth, in that order. Given an array like that, it computes a position log."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "p130.location.add_deviation(dev[:, :3], td=2618.3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The columns in the position log are _x_ offset, _y_ offset, and TVD."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 4.71237821e-02, 1.79999178e+01],\n",
       "       [0.00000000e+00, 1.86748917e-01, 3.79994202e+01],\n",
       "       [0.00000000e+00, 5.18340431e-01, 5.69962853e+01],\n",
       "       [0.00000000e+00, 1.29577626e+00, 8.39850594e+01]])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p130.location.position[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 6.45933639e-01,  3.47023772e-01, -1.65395432e-02],\n",
       "       [ 5.90396925e-01,  3.28218888e-01, -2.63643779e+00],\n",
       "       [ 5.36457735e-01,  3.11968468e-01, -5.25632568e+00],\n",
       "       ...,\n",
       "       [-3.68094384e+00,  3.97484953e+01, -2.61112780e+03],\n",
       "       [-3.68832058e+00,  3.96833189e+01, -2.61374906e+03],\n",
       "       [-3.69619567e+00,  3.96172858e+01, -2.61637033e+03]])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p130.location.trajectory()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 196.743x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p130.location.plot_plan()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p130.location.plot_3d()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quick plot\n",
    "\n",
    "`welly` produces `matplotlib` plots easily... but they aren't all that pretty. You can pass in an Axes object as `ax`, and you can embellish the plots by adding more `matplotlib` commands.\n",
    "\n",
    "First, let's do the simplest thing possible:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "p130.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since we have a position log, it's worth plotting TVD as well (though it's almost the same as MD in this well)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x864 with 5 Axes>"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tracks = ['MD', 'GR', 'RHOB', ['M2R1', 'M2R9'], 'TVD']\n",
    "\n",
    "p130.plot(tracks=tracks)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can control the plotting style, but it requires a `striplog.Legend`. We find the easiest way to build one is with a CSV-like text string:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x864 with 5 Axes>"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from striplog import Legend\n",
    "\n",
    "curve_legend_csv = \"\"\"curve mnemonic, colour,    lw,  ls,    xlim, xscale\n",
    "                      GR,             #ff0000,   1.0,  -, \"0,200\", linear\n",
    "                      RHOB,           gray,      1.0, --,        , linear\n",
    "                      M2R9,           darkgreen, 1.0,  -,        , log\n",
    "                      M2R1,           lightgreen,1.0,  -,        , log\n",
    "\"\"\"\n",
    "legend = Legend.from_csv(text=curve_legend_csv)\n",
    "\n",
    "tracks = ['MD', 'GR', 'RHOB', ['M2R1', 'M2R9'], 'TVD']\n",
    "\n",
    "p130.plot(tracks=tracks, legend=legend)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Export curves to data matrix\n",
    "\n",
    "Make a NumPy array out of the Curves in the well:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/matt/miniconda3/envs/welly/lib/python3.9/site-packages/welly/well.py:1094: UserWarning: In the next release, return_meta will be True by default. Set it to False to suppress this message. Set it to True to start using this feature now.\n",
      "  warnings.warn(message)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p130.data_as_matrix()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can use aliases here, and it's helpful to know which curve is which. You can also start and stop at new depths, to cut out the NaNs:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "alias = {'Gamma': ['GRC', 'GR', 'GRX'],\n",
    "         'Density': ['RHOZ', 'RHOB'],\n",
    "        }\n",
    "\n",
    "X, depth, features = p130.data_as_matrix(keys=['Gamma', 'Density', 'DT'],\n",
    "                                         alias=alias,\n",
    "                                         start=1200, step=1,\n",
    "                                         return_meta=True\n",
    "                                        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2624, 3)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1200., 1201., 1202., ..., 3821., 3822., 3823.])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "depth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Gamma', 'Density', 'DT']"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Export curves to pandas\n",
    "\n",
    "You can always get the curve data as a DataFrame. The depth will be the index:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = p130.df()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CALI</th>\n",
       "      <th>DT</th>\n",
       "      <th>NPHI_SAN</th>\n",
       "      <th>NPHI_LIM</th>\n",
       "      <th>NPHI_DOL</th>\n",
       "      <th>DPHI_LIM</th>\n",
       "      <th>DPHI_SAN</th>\n",
       "      <th>DPHI_DOL</th>\n",
       "      <th>M2R9</th>\n",
       "      <th>M2R6</th>\n",
       "      <th>M2R3</th>\n",
       "      <th>M2R2</th>\n",
       "      <th>M2R1</th>\n",
       "      <th>GR</th>\n",
       "      <th>SP</th>\n",
       "      <th>PEF</th>\n",
       "      <th>DRHO</th>\n",
       "      <th>RHOB</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DEPT</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20.1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20.2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20.3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20.4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20.5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      CALI  DT  NPHI_SAN  NPHI_LIM  NPHI_DOL  DPHI_LIM  DPHI_SAN  DPHI_DOL  \\\n",
       "DEPT                                                                         \n",
       "20.1   NaN NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "20.2   NaN NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "20.3   NaN NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "20.4   NaN NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "20.5   NaN NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "\n",
       "      M2R9  M2R6  M2R3  M2R2  M2R1  GR  SP  PEF  DRHO  RHOB  \n",
       "DEPT                                                         \n",
       "20.1   NaN   NaN   NaN   NaN   NaN NaN NaN  NaN   NaN   NaN  \n",
       "20.2   NaN   NaN   NaN   NaN   NaN NaN NaN  NaN   NaN   NaN  \n",
       "20.3   NaN   NaN   NaN   NaN   NaN NaN NaN  NaN   NaN   NaN  \n",
       "20.4   NaN   NaN   NaN   NaN   NaN NaN NaN  NaN   NaN   NaN  \n",
       "20.5   NaN   NaN   NaN   NaN   NaN NaN NaN  NaN   NaN   NaN  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='DEPT'>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.GR.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To get the UWI of the well as well, e.g. if you want to combine multiple wells:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>CALI</th>\n",
       "      <th>DT</th>\n",
       "      <th>NPHI_SAN</th>\n",
       "      <th>NPHI_LIM</th>\n",
       "      <th>NPHI_DOL</th>\n",
       "      <th>DPHI_LIM</th>\n",
       "      <th>DPHI_SAN</th>\n",
       "      <th>DPHI_DOL</th>\n",
       "      <th>M2R9</th>\n",
       "      <th>M2R6</th>\n",
       "      <th>M2R3</th>\n",
       "      <th>M2R2</th>\n",
       "      <th>M2R1</th>\n",
       "      <th>GR</th>\n",
       "      <th>SP</th>\n",
       "      <th>PEF</th>\n",
       "      <th>DRHO</th>\n",
       "      <th>RHOB</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UWI</th>\n",
       "      <th>DEPT</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">100/N14A/11E05</th>\n",
       "      <th>20.1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20.2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20.3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20.4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20.5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     CALI  DT  NPHI_SAN  NPHI_LIM  NPHI_DOL  DPHI_LIM  \\\n",
       "UWI            DEPT                                                     \n",
       "100/N14A/11E05 20.1   NaN NaN       NaN       NaN       NaN       NaN   \n",
       "               20.2   NaN NaN       NaN       NaN       NaN       NaN   \n",
       "               20.3   NaN NaN       NaN       NaN       NaN       NaN   \n",
       "               20.4   NaN NaN       NaN       NaN       NaN       NaN   \n",
       "               20.5   NaN NaN       NaN       NaN       NaN       NaN   \n",
       "\n",
       "                     DPHI_SAN  DPHI_DOL  M2R9  M2R6  M2R3  M2R2  M2R1  GR  SP  \\\n",
       "UWI            DEPT                                                             \n",
       "100/N14A/11E05 20.1       NaN       NaN   NaN   NaN   NaN   NaN   NaN NaN NaN   \n",
       "               20.2       NaN       NaN   NaN   NaN   NaN   NaN   NaN NaN NaN   \n",
       "               20.3       NaN       NaN   NaN   NaN   NaN   NaN   NaN NaN NaN   \n",
       "               20.4       NaN       NaN   NaN   NaN   NaN   NaN   NaN NaN NaN   \n",
       "               20.5       NaN       NaN   NaN   NaN   NaN   NaN   NaN NaN NaN   \n",
       "\n",
       "                     PEF  DRHO  RHOB  \n",
       "UWI            DEPT                   \n",
       "100/N14A/11E05 20.1  NaN   NaN   NaN  \n",
       "               20.2  NaN   NaN   NaN  \n",
       "               20.3  NaN   NaN   NaN  \n",
       "               20.4  NaN   NaN   NaN  \n",
       "               20.5  NaN   NaN   NaN  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = p130.df(uwi=True)\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you have several wells, you can also use `welly.Project.df()` to do the concatenation for you.\n",
    "\n",
    "Note that you can also use aliases with the DataFrame creation, or create a new 'basis' (depth in this case):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CALI</th>\n",
       "      <th>Gamma</th>\n",
       "      <th>Density</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DEPT</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20.1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20.2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20.3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20.4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20.5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      CALI  Gamma  Density\n",
       "DEPT                      \n",
       "20.1   NaN    NaN      NaN\n",
       "20.2   NaN    NaN      NaN\n",
       "20.3   NaN    NaN      NaN\n",
       "20.4   NaN    NaN      NaN\n",
       "20.5   NaN    NaN      NaN"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "keys = ['CALI', 'Gamma', 'Density']\n",
    "df = p130.df(keys=keys, alias=alias, rename_aliased=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Make an 'empty' well"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>original_mnemonic</th>\n",
       "      <th>mnemonic</th>\n",
       "      <th>unit</th>\n",
       "      <th>value</th>\n",
       "      <th>descr</th>\n",
       "      <th>section</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [original_mnemonic, mnemonic, unit, value, descr, section]\n",
       "Index: []"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import welly\n",
    "\n",
    "w = welly.Well()\n",
    "\n",
    "w.header  # is empty"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can set the **UWI** and **name** of a well directly on the well object, but these are the only attributes of the well we can set in this way."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'foo'"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w.uwi = 'foo'\n",
    "w.uwi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>original_mnemonic</th>\n",
       "      <th>mnemonic</th>\n",
       "      <th>unit</th>\n",
       "      <th>value</th>\n",
       "      <th>descr</th>\n",
       "      <th>section</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>UWI</td>\n",
       "      <td>UWI</td>\n",
       "      <td>None</td>\n",
       "      <td>foo</td>\n",
       "      <td>None</td>\n",
       "      <td>header</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  original_mnemonic mnemonic  unit value descr section\n",
       "0               UWI      UWI  None   foo  None  header"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w.header"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "&copy; 2022 Agile Scientific, CC BY"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "welly",
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    "name": "ipython",
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